Facial emotion recognition in Parkinson's disease: A review and new hypotheses

Social cognition training improves recognition of distinct facial emotions and decreases misattribution errors in healthy individuals

Facial emotion recognition is a key component of social cognition. Impaired facial emotion recognition is tied to poor psychological wellbeing and deficient social functioning. While previous research has demonstrated the potential for social cognition training to improve overall facial emotion recognition, questions remain regarding what aspects of emotion recognition improve. We report results from a randomized controlled trial that evaluates whether computerized social cognition training can improve recognition of distinct facial emotions in healthy participants. This investigation was designed to better understand the therapeutic potential of social cognition training for individuals with neuropsychiatric disorders. Fifty-five healthy adult participants were randomly assigned to an internet-based intervention during which they either completed social cognition training (SCT) or played control computer games (CON) for 10.5 h over 2-3 weeks. Facial emotion recognition was measured with the Penn ER-40, which was conducted before and after training. The following variables were collected and analyzed: facial emotion recognition accuracy for each emotion (i.e., anger, fear, happy, neutral (no emotional expression), and sad), reaction times for each emotion, and response error types (i.e., frequency of an emotion being chosen incorrectly, frequency of an emotion being missed, and frequency of an emotion being confused for another particular emotion). ANOVAs and t-tests were used to elucidate intervention effects both within and between groups. Results showed that the SCT group improved their accuracy for angry and neutral faces. They also improved their reaction times for neutral, fearful, and sad faces. Compared to the CON group, the SCT group had significantly faster reaction times to neutral faces after training. Lastly, the SCT group decreased their tendency to confuse angry faces for no emotional expression and to confuse no emotional expression for sad faces. In contrast, the CON group did not significantly improve their accuracy or reaction times on any emotional expression, and they did not improve their response error types. We conclude that social cognition training can improve recognition of distinct emotions in healthy participants and decrease response error patterns, suggesting it has the potential to improve impaired emotion recognition and social functioning in individuals with facial emotion recognition deficits.

Effects of emotional valence and intensity on cognitive and affective empathy after insula lesions

The insula plays a central role in empathy. However, the complex structure of cognitive (CE) and affective empathy (AE) deficits following insular damage is not fully understood. In the present study, patients with insular lesions (n = 20) and demographically matched healthy controls (n = 24) viewed ecologically valid videos that varied in terms of valence and emotional intensity. The videos showed a person (target) narrating a personal life event. In CE conditions, subjects continuously rated the affective state of the target, while in AE conditions, they continuously rated their own affect. Mean squared error (MSE) assessed deviations between subject and target ratings. Patients differed from controls only in negative, low-intensity AE, rating their own affective state less negative than the target. This deficit was not related to trait empathy, neuropsychological or clinical parameters, or laterality of lesion. Empathic functions may be widely spared after insular damage in a naturalistic, dynamic setting, potentially due to the intact interpretation of social context by residual networks outside the lesion. The particular role of the insula in AE for negative states may evolve specifically in situations that bear higher uncertainty pointing to a threshold role of the insula in online ratings of AE.

Mild cognitive impairment in patients with Parkinson’s disease: An updated mini-review and future outlook

Mild cognitive impairment (MCI) is one of the common non-motor symptoms in patients with Parkinson’s disease (PD). MCI is the transition stage between normal aging and full-blown dementia and is also a powerful predictor of dementia. Although the concept of MCI has been used to describe some of the PD symptoms for many years, there is a lack of consistent diagnostic criteria. Moreover, because of the diverse patterns of the cognitive functions, each cognitive impairment will have a different progression. In this review, we overviewed the diagnostic criteria for PD-MCI, primarily focused on the heterogeneity of PD-MCI patients’ cognitive function, including various types of cognitive functions and their progression rates. A review of this topic is expected to be beneficial for clinical diagnosis, early intervention, and treatment. In addition, we also discussed the unmet needs and future vision in this field.

Social decision-making in Parkinson's disease

INTRODUCTION

Parkinson's Disease (PD) commonly affects cognition and communicative functions, including the ability to perceive socially meaningful cues from nonverbal behavior and spoken language (e.g., a speaker's tone of voice). However, we know little about how people with PD use social information to make decisions in daily interactions (e.g., decisions to trust another person) and whether this ability rests on intact cognitive functions and executive/decision-making abilities in nonsocial domains.

METHOD

Non-demented adults with and without PD were presented utterances that conveyed differences in speaker confidence or politeness based on the way that speakers formulated their statement and their tone of voice. Participants had to use these speech-related cues to make trust-related decisions about interaction partners while playing the Trust Game. Explicit measures of social perception, nonsocial decision-making, and related cognitive abilities were collected.

RESULTS

Individuals with PD displayed significant differences from control participants in social decision-making; for example, they showed greater trust in game partners whose voice sounded confident and who explicitly stated that they would cooperate with the participant. The PD patients displayed relative intact social perception (speaker confidence or politeness ratings) and were unimpaired on a nonsocial decision-making task (the Dice game). No obvious relationship emerged between measures of social perception, social decision-making, or cognitive functioning in the PD sample.

CONCLUSIONS

Results provide evidence of alterations in decision-making restricted to social contexts in PD individuals with relatively preserved cognition with minimal changes in social perception. Researchers and practitioners interested in how PD affects social perception and cognition should include assessments that emulate social interactions, as non-interactive tasks may fail to detect the full impact of the disease on those affected.

Posterior-prefrontal and medial orbitofrontal regions play crucial roles in happiness and sadness recognition

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Brain areas underlying trade-off relations between emotions were identified.

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Damage to the PPF area reduces accuracy of happiness recognition.

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Damage to the PPF increases accuracy of sadness recognition.

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A similar tendency was observed in orbitofrontal regions for sadness recognition.

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Only a deficit in sadness, but not happiness, persisted in the chronic phase.

The core brain regions responsible for basic human emotions are not yet fully understood. We investigated the key areas responsible for emotion recognition of facial expressions of happiness and sadness using data obtained from patients who underwent local brain resection. A total of 44 patients with right cerebral hemispheric brain tumors and 33 healthy volunteers were enrolled and subjected to a facial expression recognition test. Voxel-based lesion-symptom mapping was performed to investigate the relationship between the accuracy of emotion recognition and the resected regions. Consequently, trade-off relationships were discovered: the posterior-prefrontal region was related to a low score of happiness recognition and a high score of sadness recognition (disorder-of-happiness group), whereas the medial orbitofrontal region was related to a low score of sadness recognition and a high score of happiness recognition (disorder-of-sadness group). The emotion recognition score in both the happiness and sadness disorder groups was significantly lower than that in the control group (p = 0.0009 and p = 0.021, respectively). Interestingly, the deficit in happiness recognition was temporary, whereas the deficit in sadness recognition persisted during the chronic phase. Using graph theoretical analysis, we identified structural connectivity between the posterior-prefrontal and medial orbitofrontal regions. When either of these regions was damaged, the tract volume connecting them was significantly reduced (p = 0.013). These results indicate that the posterior-prefrontal and medial orbitofrontal regions may be crucial for maintaining a balance between happiness and sadness recognition in humans. Investigating the clinical impact of certain area resections using lesion studies combined with connectivity analysis is a useful neuroimaging method for understanding neural networks.

Can AI make people happy? The effect of AI-based chatbot on smile and speech in Parkinson's disease

INTRODUCTION

Approaches for objectively measuring facial expressions and speech may enhance clinical and research evaluation in telemedicine, which is widely employed for Parkinson's disease (PD). This study aimed to assess the feasibility and efficacy of using an artificial intelligence-based chatbot to improve smile and speech in PD. Further, we explored the potential predictive value of objective face and speech parameters for motor symptoms, cognition, and mood.

METHODS

In this open-label randomized study, we collected a series of face and conversational speech samples from 20 participants with PD in weekly teleconsultation sessions for 5 months. We investigated the effect of daily chatbot conversations on smile and speech features, then we investigated whether smile and speech features could predict motor, cognitive, and mood status.

RESULTS

A repeated-measures analysis of variance revealed that the chatbot conversations had a significant interaction effect on the mean and standard deviation of the smile index during smile sections (both P = .02), maximum duration of the initial rise of the smile index (P = .04), and frequency of filler words (P = .04), but no significant interaction effects were observed for clinical measurements including motor, cognition, depression, and quality of life. Explorative analysis using statistical and machine-learning models revealed that the smile indices and several speech features were associated with motor symptoms, cognition, and mood in PD.

CONCLUSION

An artificial intelligence-based chatbot may positively affect smile and speech in PD. Smile and speech features may capture the motor, cognitive, and mental status of patients with PD.

Dopaminergic Modulation of Dynamic Emotion Perception

Emotion recognition abilities are fundamental to our everyday social interaction. A large number of clinical populations show impairments in this domain, with emotion recognition atypicalities being particularly prevalent among disorders exhibiting a dopamine system disruption (e.g., Parkinson's disease). Although this suggests a role for dopamine in emotion recognition, studies employing dopamine manipulation in healthy volunteers have exhibited mixed neural findings and no behavioral modulation. Interestingly, while a dependence of dopaminergic drug effects on individual baseline dopamine function has been well established in other cognitive domains, the emotion recognition literature so far has failed to account for these possible interindividual differences. The present within-subjects study therefore tested the effects of the dopamine D2 antagonist haloperidol on emotion recognition from dynamic, whole-body stimuli while accounting for interindividual differences in baseline dopamine. A total of 33 healthy male and female adults rated emotional point-light walkers (PLWs) once after ingestion of 2.5 mg haloperidol and once after placebo. To evaluate potential mechanistic pathways of the dopaminergic modulation of emotion recognition, participants also performed motoric and counting-based indices of temporal processing. Confirming our hypotheses, effects of haloperidol on emotion recognition depended on baseline dopamine function, where individuals with low baseline dopamine showed enhanced, and those with high baseline dopamine decreased emotion recognition. Drug effects on emotion recognition were related to drug effects on movement-based and explicit timing mechanisms, indicating possible mediating effects of temporal processing. Results highlight the need for future studies to account for baseline dopamine and suggest putative mechanisms underlying the dopaminergic modulation of emotion recognition.SIGNIFICANCE STATEMENT A high prevalence of emotion recognition difficulties among clinical conditions where the dopamine system is affected suggests an involvement of dopamine in emotion recognition processes. However, previous psychopharmacological studies seeking to confirm this role in healthy volunteers thus far have failed to establish whether dopamine affects emotion recognition and lack mechanistic insights. The present study uncovered effects of dopamine on emotion recognition in healthy individuals by controlling for interindividual differences in baseline dopamine function and investigated potential mechanistic pathways via which dopamine may modulate emotion recognition. Our findings suggest that dopamine may influence emotion recognition via its effects on temporal processing, providing new directions for future research on typical and atypical emotion recognition.

Deficits in Emotion Recognition and Theory of Mind in Parkinson's Disease Patients With and Without Cognitive Impairments

Background

Emotion recognition and social deficits have been previously reported in Parkinson's disease (PD). However, the extent of these impairments is still unclear and social cognition is excluded from the cognitive domains considered in the current criteria for PD mild cognitive impairment (MCI). This study aims to analyze emotion recognition, affective and cognitive theory of mind in early PD patients classified according to Level II MCI criteria, and to evaluate the prevalence of socio-cognitive deficits in this sample.

Methods

We enrolled 45 participants with PD, classified as cognitively unimpaired (CU; n = 32) or MCI (n = 13) based on a standard neuropsychological assessment. Social cognitive skills were evaluated through validated tests for emotion recognition (i.e., Ekman 60-faces test, Ek60 Test) and mental states attribution (Story-based Empathy Task, SET) and compared to a group of 45 healthy controls (HC). Between-group differences in social tasks were performed, as well as correlation analyses to assess the relationship between social, cognitive, and clinical variables. Finally, the number of patients with social cognitive impairments in both MCI and CU subgroups was computed based on Italian normative data.

Results

Statistical comparison revealed significant differences among groups in the Ek60 test, with MCI obtaining significantly lower scores than HC and CU, especially for negative emotions. Significant differences were detected also in the SET, with lower performance in emotion and intention attribution for both PD groups compared to HC. A significant correlation emerged between the Ek60 test and emotion attribution. Nine patients showed poor performance at social tasks, five of them being classified as PD-CU.

Discussion

Parkinson's disease cognitive profile was characterized by emotion recognition and attribution deficits. These results, as well as the detection of CU patients with isolated socio-cognitive impairments, underline the importance of assessing social cognition in PD as a possible early marker of cognitive decline.

Action and emotion perception in Parkinson's disease: A neuroimaging meta-analysis

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The neural substrates for action and emotion perception deficits in PD are still unclear.

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We addressed this issue via coordinate-based meta-analyses of previous fMRI data.

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PD patients exhibit decreased response in the basal ganglia.

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PD patients exhibit a trend toward decreased response in the parietal areas.

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PD patients exhibit a trend toward increased activation in the posterior cerebellum.

Patients with Parkinson disease (PD) may show impairments in the social perception. Whether these deficits have been consistently reported, it remains to be clarified which brain alterations subtend them. To this aim, we conducted a neuroimaging meta-analysis to compare the brain activity during social perception in patients with PD versus healthy controls. Our results show that PD patients exhibit a significantly decreased response in the basal ganglia (putamen and pallidum) and a trend toward decreased activity in the mirror system, particularly in the left parietal cortex (inferior parietal lobule and intraparietal sulcus). This reduced activation may be tied to a disruption of cognitive resonance mechanisms and may thus constitute the basis of impaired others’ representations underlying action and emotion perception. We also found increased activation in the posterior cerebellum in PD, although only in a within-group analysis and not in comparison with healthy controls. This cerebellar activation may reflect compensatory mechanisms, an aspect that deserves further investigation. We discuss the clinical implications of our findings for the development of novel social skill training programs for PD patients.

Hypomimia May Influence the Facial Emotion Recognition Ability in Patients with Parkinson's Disease

BACKGROUND

Hypomimia is a clinical feature of Parkinson's disease (PD). Based on the embodied simulation theory, the impairment of facial mimicry may worsen facial emotion recognition; however, the empirical results are inconclusive.

OBJECTIVE

We aimed to explore the worsening of emotion recognition by hypomimia. We further explored the relationship between the hypomimia, emotion recognition, and social functioning.

METHODS

A total of 114 participants were recruited. The patients with PD and normal controls (NCs) were matched for demographic characteristics. All the participants completed the Mini-Mental State Examination and the Chinese Multi-modalities Emotion Recognition Test. In addition to the above tests, the patients were assessed with the Movement Disorder Society-Unified Parkinson's Disease Rating Scale and Parkinson's Disease Social Functioning Scale (PDSFS).

RESULTS

Patients with PD with hypomimia had worse recognition of disgust than NCs (p = 0.018). The severity of hypomimia was predictive of the recognition of disgust (β= -0.275, p = 0.028). Facial emotion recognition was predictive of the PDSFS score of PD patients (β= 0.433, p = 0.001). We also found that recognizing disgust could mediate the relationship between hypomimia and the PDSFS score (β= 0.264, p = 0.045).

CONCLUSION

Patients with hypomimia had the worst disgust facial recognition. Hypomimia may affect the social function of PD patients, which is related to recognizing the expression of disgust. Emotion recognition training may improve the social function of patients with PD.

EEG-based emotion charting for Parkinson's disease patients using Convolutional Recurrent Neural Networks and cross dataset learning

Electroencephalogram (EEG) based emotion classification reflects the actual and intrinsic emotional state, resulting in more reliable, natural, and meaningful human-computer interaction with applications in entertainment consumption behavior, interactive brain-computer interface, and monitoring of psychological health of patients in the domain of e-healthcare. Challenges of EEG-based emotion recognition in real-world applications are variations among experimental settings and cognitive health conditions. Parkinson's Disease (PD) is the second most common neurodegenerative disorder, resulting in impaired recognition and expression of emotions. The deficit of emotional expression poses challenges for the healthcare services provided to PD patients. This study proposes 1D-CRNN-ELM architecture, which combines one-dimensional Convolutional Recurrent Neural Network (1D-CRNN) with an Extreme Learning Machine (ELM), robust for the emotion detection of PD patients, also available for cross dataset learning with various emotions and experimental settings. In the proposed framework, after EEG preprocessing, the trained CRNN can use as a feature extractor with ELM as the classifier, and again this trained CRNN can be used for learning of new emotions set with fine-tuning of other datasets. This paper also applied cross dataset learning of emotions by training with PD patients datasets and fine-tuning with publicly available datasets of AMIGOS and SEED-IV, and vice versa. Random splitting of train and test data with 80 - 20 ratio resulted in an accuracy of 97.75% for AMIGOS, 83.20% for PD, and 86.00% for HC with six basic emotion classes. Fine-tuning of trained architecture with four emotions of the SEED-IV dataset results in 92.5% accuracy. To validate the generalization of our results, leave one subject (patient) out cross-validation is also incorporated with mean accuracies of 95.84% for AMIGOS, 75.09% for PD, 77.85% for HC, and 84.97% for SEED-IV is achieved. Only a 1 - sec segment of EEG signal from 14 channels is enough to detect emotions with this performance. The proposed method outperforms state-of-the-art studies to classify EEG-based emotions with publicly available datasets, provide cross dataset learning, and validate the robustness of the deep learning framework for real-world application of psychological healthcare monitoring of Parkinson's disease patients.

Quantitative Evaluation of Hypomimia in Parkinson's Disease: A Face Tracking Approach

Parkinson's disease (PD) is a neurological disorder that mainly affects the motor system. Among other symptoms, hypomimia is considered one of the clinical hallmarks of the disease. Despite its great impact on patients' quality of life, it remains still under-investigated. The aim of this work is to provide a quantitative index for hypomimia that can distinguish pathological and healthy subjects and that can be used in the classification of emotions. A face tracking algorithm was implemented based on the Facial Action Coding System. A new easy-to-interpret metric (face mobility index, FMI) was defined considering distances between pairs of geometric features and a classification based on this metric was proposed. Comparison was also provided between healthy controls and PD patients. Results of the study suggest that this index can quantify the degree of impairment in PD and can be used in the classification of emotions. Statistically significant differences were observed for all emotions when distances were taken into account, and for happiness and anger when FMI was considered. The best classification results were obtained with Random Forest and kNN according to the AUC metric.

White matter microstructures in Parkinson's disease with and without impulse control behaviors

BACKGROUND

Impulse control behaviors (ICBs) in Parkinson's disease (PD) are thought to be caused by an overdose of dopaminergic therapy in the relatively spared ventral striatum, or by hypersensitivity of this region to dopamine. Alterations in brain networks are now also thought to contribute to the development of ICBs.

OBJECTIVE

To comprehensively assess white matter microstructures in PD patients with ICBs using advanced diffusion MRI and magnetization transfer saturation (MT-sat) imaging.

METHODS

This study included 19 PD patients with ICBs (PD-ICBs), 18 PD patients without ICBs (PD-nICBs), and 20 healthy controls (HCs). Indices of diffusion tensor imaging (DTI), diffusion kurtosis imaging, neurite orientation dispersion and density imaging, and MT-sat imaging were evaluated using tract-based spatial statistics (TBSS), regions of interest (ROIs), and tract-specific analysis (TSA).

RESULTS

Compared with HCs, PD-nICBs had significant alterations in many major white matter tracts in most parameters. In contrast, PD-ICBs had only partial changes in several parameters. Compared with PD-ICBs, TBSS, ROI, and TSA analyses revealed that PD-nICBs had lower axial kurtosis, myelin volume fraction, and orientation dispersion index in the uncinate fasciculus and external capsule, as well as in the retrolenticular part of the internal capsule. These are components of the reward system and the visual and emotional perception areas, respectively.

INTERPRETATION

Myelin and axonal changes in fibers related to the reward system and visual emotional recognition might be more prominent in PD-nICBs than in PD-ICBs.

Private Facial Prediagnosis as an Edge Service for Parkinson's DBS Treatment Valuation

Facial phenotyping for medical prediagnosis has recently been successfully exploited as a novel way for the preclinical assessment of a range of rare genetic diseases, where facial biometrics is revealed to have rich links to underlying genetic or medical causes. In this paper, we aim to extend this facial prediagnosis technology for a more general dis-ease, Parkinson's Diseases (PD), and proposed an Artificial-Intelligence-of-Things (AIoT) edge-oriented privacy-preserving facial prediagnosis framework to analyze the treatment of Deep Brain Stimulation (DBS) on PD patients. In the proposed framework, a novel edge-based privacy-preserving framework is proposed to implement private deep facial diagnosis as a service over an AIoT-oriented information theoretically secure multi-party communication scheme, where partial homomorphic encryption (PHE) is leveraged to enable privacy-preserving deep facial diagnosis on encrypted facial patterns. In our experiments with a collected facial dataset from PD patients, for the first time, we proved that facial patterns could be used to evaluate the facial difference of PD patients undergoing DBS treatment. We further implemented a privacy-preserving information theoretical secure deep facial prediagnosis framework that can achieve the same accuracy as the non-encrypted one, showing the potential of our facial prediagnosis as a trust-worthy edge service for grading the severity of PD in patients.

Moving beyond emotions in Parkinson's disease

OBJECTIVE

Emotion recognition is a fundamental neurocognitive capacity that is a critical predictor of interpersonal function and, in turn, mental health. Although people with Parkinson's disease (PD) often exhibit difficulties recognizing emotions, almost all studies to date have focused on basic emotions (happiness, sadness, anger, surprise, fear, and disgust), with little consideration of how more cognitively complex self-conscious emotions such as contempt, embarrassment, and pride might also be affected. Further, the few studies that have considered self-conscious emotions have relied on high intensity, static stimuli. The aim of the present study was to therefore provide the first examination of how self-conscious emotion recognition is affected by PD using a dynamic, dual-intensity measure that more closely captures how emotion recognition judgements are made in daily life.

METHOD

People with PD (n = 42) and neurotypical controls (n = 42) completed a validated measure of self-conscious facial emotion recognition. For comparative purposes, in addition to a broader clinical test battery, both groups also completed a traditional static emotion recognition measure and a measure of self-conscious emotional experience.

RESULTS

Relative to controls, the PD group did not differ in their capacity to recognize basic emotions but were impaired in their recognition of self-conscious emotions. These difficulties were associated with elevated negative affect and poorer subjective well-being.

CONCLUSIONS

Difficulties recognizing self-conscious emotions may be more problematic for people with PD than difficulties recognizing basic ones, with implications for interventions focused on helping people with this disorder develop and maintain strong social networks.

PRACTITIONER POINTS

This is the first direct investigation into how the recognition of self-conscious emotion is affected in Parkinson's disease using dynamic, dual-intensity stimuli, thus providing an important extension to prior literature that has focused solely on basic emotion recognition and/or relied on static, high-intensity stimuli. Results revealed preserved basic facial emotional recognition coexisting with impairment in all three self-conscious emotions assessed, therefore suggesting that the latter stimuli type may function as a more sensitive indicator of Parkinson's disease-related social cognitive impairment. Problems with self-conscious emotion recognition in people with Parkinson's disease were associated with poorer broader subjective well-being and increased negative affect. This aligns with the broader literature linking interpersonal difficulties with poorer clinical outcomes in this cohort.

No Higher Risk-Seeking Tendencies or Altered Self-Estimation in a Social Decision-Making Task in Patients with Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) has been associated with a tendency towards more risky decisions. However, the commonly used paradigms typically neglect the social context.

OBJECTIVE

Here, we investigated social decision-making and self-estimation in a competitive experimental task.

METHODS

A computerized experimental setting was used in which 86 PD patients (age = 66.5 [50-79], 62.8% male, H&Y = 2 [1.5-3]) and 44 healthy controls (HC; age = 67 [54-79], 54.4% male) in groups of four performed mathematical addition tasks in which they were asked to calculate as many sums as possible in five minutes. Participants had to choose their preferred compensation scheme ("piece rate" versus "tournament") and retrospectively rank their performance in comparison to the suspected performance of the others. A comprehensive neuropsychological test battery was also conducted.

RESULTS

No significant difference was found in overall social decision-making and self-estimation between PD patients and HC. However, for those individuals who made inadequate decisions, PD patients engaged in significantly more risk-averse and HC in more risky decisions. Concerning those inadequate decisions, the PD patients made more extreme decisions (severity of social decision-making) in both directions (risk-averse, risk-seeking).

CONCLUSION

Our data indicate that social decision-making behavior and self-estimation are largely intact in PD patients with mild to moderate disease stages and intact global cognition, executive functions, and social cognition. Future studies with more heterogeneous PD samples regarding their neuropsychological profile will have to examine at which state social decision-making may be affected and by which factors this behavior might be influenced.

Deficits in emotion perception and cognition in patients with parkinson's disease: A systematic review

Non-motor symptoms (NMS) are common among Parkinson's disease (PD) patients and have a significant impact on quality of life. NMS such as deficits in emotion perception are gaining due focus in the recent times. As emotion perception and cognitive functions share certain common neural substrates, it becomes pertinent to evaluate existing emotion perception deficits in view of underlying cognitive deficits. The current systematic review aimed at examining studies on emotion perception PD in the last decade. We carried out a systematic review of 44 studies from the PubMed database. We reviewed studies examining emotion perception and associated cognitive deficits, especially executive function and visuospatial function in PD. This review also examines how early and advanced PD differ in emotion perception deficits and how the presence of common neuropsychiatric conditions such as anxiety, apathy, and depression as well as neurosurgical procedure such as deep brain stimulation affect emotion perception. The need for future research employing a comprehensive evaluation of neurocognitive functions and emotion perception is underscored as it has a significant bearing on planning holistic intervention strategies.

A Proposal for Multimodal Emotion Recognition Using Aural Transformers and Action Units on RAVDESS Dataset

Emotion recognition is attracting the attention of the research community due to its multiple applications in different fields, such as medicine or autonomous driving. In this paper, we proposed an automatic emotion recognizer system that consisted of a speech emotion recognizer (SER) and a facial emotion recognizer (FER). For the SER, we evaluated a pre-trained xlsr-Wav2Vec2.0 transformer using two transfer-learning techniques: embedding extraction and fine-tuning. The best accuracy results were achieved when we fine-tuned the whole model by appending a multilayer perceptron on top of it, confirming that the training was more robust when it did not start from scratch and the previous knowledge of the network was similar to the task to adapt. Regarding the facial emotion recognizer, we extracted the Action Units of the videos and compared the performance between employing static models against sequential models. Results showed that sequential models beat static models by a narrow difference. Error analysis reported that the visual systems could improve with a detector of high-emotional load frames, which opened a new line of research to discover new ways to learn from videos. Finally, combining these two modalities with a late fusion strategy, we achieved 86.70% accuracy on the RAVDESS dataset on a subject-wise 5-CV evaluation, classifying eight emotions. Results demonstrated that these modalities carried relevant information to detect users’ emotional state and their combination allowed to improve the final system performance.

Multimodal Emotion Recognition on RAVDESS Dataset Using Transfer Learning

Emotion Recognition is attracting the attention of the research community due to the multiple areas where it can be applied, such as in healthcare or in road safety systems. In this paper, we propose a multimodal emotion recognition system that relies on speech and facial information. For the speech-based modality, we evaluated several transfer-learning techniques, more specifically, embedding extraction and Fine-Tuning. The best accuracy results were achieved when we fine-tuned the CNN-14 of the PANNs framework, confirming that the training was more robust when it did not start from scratch and the tasks were similar. Regarding the facial emotion recognizers, we propose a framework that consists of a pre-trained Spatial Transformer Network on saliency maps and facial images followed by a bi-LSTM with an attention mechanism. The error analysis reported that the frame-based systems could present some problems when they were used directly to solve a video-based task despite the domain adaptation, which opens a new line of research to discover new ways to correct this mismatch and take advantage of the embedded knowledge of these pre-trained models. Finally, from the combination of these two modalities with a late fusion strategy, we achieved 80.08% accuracy on the RAVDESS dataset on a subject-wise 5-CV evaluation, classifying eight emotions. The results revealed that these modalities carry relevant information to detect users' emotional state and their combination enables improvement of system performance.

Age-of-actor effects in body expression recognition of children

Investigations of developmental trajectories for emotion recognition suggest that both face- and body expression recognition increases rapidly in early childhood and reaches adult levels of performance near the age of ten. So far, little is known about whether children's ability to recognise body expressions is influenced by the age of the person they are observing. This question is investigated here by presenting 119 children and 42 young adults with videos of children, young adults and older adults expressing emotions with their whole body. The results revealed an own-age advantage for children, reflected in adult-level accuracy for videos of children for most expressions but reduced accuracy for videos of older adults. Children's recognition of older adults' expressions was not correlated with children's estimated amount of contact with older adults. Support for potential influences of social biases on performance measures was minimal. The own-age advantage was explained in terms of children's reduced familiarity with body expressions of older adults due to aging related changes in the kinematics characteristics of movements and potentially due to stronger embodiment of other children's bodily movements.

What Do We Know about Theory of Mind Impairment in Parkinson's Disease?

Theory of mind (ToM) is a social cognitive skill that involves the ability to attribute mental states to self and others (what they think (cognitive ToM) and feel (affective ToM)). We aim to provide an overview of previous knowledge of ToM in Parkinson's disease (PD). In the last few years more attention has been paid to the study of this construct as a non-motor manifestation of PD. In advanced stages, both components of ToM (cognitive and affective) are commonly impaired, although in early PD results remain controversial. Executive dysfunction correlates with ToM deficits and other cognitive domains such as language and visuospatial function have also been related to ToM. Recent studies have demonstrated that PD patients with mild cognitive impairment show ToM deficits more frequently in comparison with cognitively normal PD patients. In addition to the heterogeneity of ToM tests administered in different studies, depression and dopaminergic medication may also be acting as confounding factors, but there are still insufficient data to support this. Neuroimaging studies conducted to understand the underlying networks of cognitive and affective ToM deficits in PD are lacking. The study of ToM deficit in PD continues to be important, as this may worsen quality of life and favor social stigma. Future studies should be considered, including assessment of the patients' cognitive state, associated mood disorders, and the role of dopaminergic deficit.

Detection of hypomimia in patients with Parkinson's disease via smile videos

Background

Parkinson’s disease (PD) is a neurodegenerative disease characterized by the impairment of facial expression, known as hypomimia. Hypomimia has serious impacts on patients’ ability to communicate, and it is difficult to detect at early stages of the disease. Furthermore, due to bradykinesia or other reasons, it is inconvenient for PD patients to visit the hospital. Therefore, it is appealing to develop an auxiliary diagnostic method that remotely detects hypomimia.

Methods

We proposed an automatic detection system for Parkinson’s hypomimia based on facial expressions (DSPH-FE). DSPH-FE provides a convenient remote service for those who potentially suffer from hypomimia and only requires patients to input their facial videos. Specifically, patients can detect hypomimia through two aspects: geometric features and texture features. Geometric features focus on visually representing structures of facial muscles. Facial expression factors (FEFs) are used as the first metric to quantify the current activation state of the facial muscles. Facial expression change factors (FECFs) are subsequently used as the second metric to calculate the moving trajectories of the activation states in the videos. Geometric features primarily concentrate on spatial information, with little involvement of temporal information. Thus, the extended histogram of oriented gradients (HOG) algorithm is introduced. This algorithm can extract texture features within multiple continuous frames and incorporate the temporal information into the features. Finally, these features are applied to four machine learning algorithms to model the relationship between these features and hypomimia.

Results

The DSPH-FE detection system achieved the best performance when concatenating geometric features and texture features, resulting in a F1 score of 0.9997. The best F1 scores achieved with geometric features and texture features were 0.8286 and 0.9446, respectively. This indicated that both geometric features and texture features have an ability to predict hypomimia, and demonstrated that temporal information can boost the model performance. Thus, DSPH-FE is an effective supportive tool in the medical management of PD patients.

Conclusions

Comprehensive experiments demonstrated that proposed features fit well with real-world videos and are beneficial in the clinical diagnosis of hypomimia. In particular, hypomimia had a greater impact on eyes and mouths when patients are smiling.

Blunted emotion judgments of body movements in Parkinson's disease

Some of the behavioral disorders observed in Parkinson’s disease (PD) may be related to an altered processing of social messages, including emotional expressions. Emotions conveyed by whole body movements may be difficult to generate and be detected by PD patients. The aim of the present study was to compare valence judgments of emotional whole body expressions in individuals with PD and in healthy controls matched for age, gender and education. Twenty-eight participants (13 PD patients and 15 healthy matched control participants) were asked to rate the emotional valence of short movies depicting emotional interactions between two human characters presented with the “Point Light Displays” technique. To ensure understanding of the perceived scene, participants were asked to briefly describe each of the evaluated movies. Patients’ emotional valence evaluations were less intense than those of controls for both positive (p < 0.001) and negative (p < 0.001) emotional expressions, even though patients were able to correctly describe the depicted scene. Our results extend the previously observed impaired processing of emotional facial expressions to impaired processing of emotions expressed by body language. This study may support the hypothesis that PD affects the embodied simulation of emotional expression and the potentially involved mirror neuron system.

Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases

Social feedback can selectively enhance learning in diverse domains. Relevant neurocognitive mechanisms have been studied mainly in healthy persons, yielding correlational findings. Neurodegenerative lesion models, coupled with multimodal brain measures, can complement standard approaches by revealing direct multidimensional correlates of the phenomenon.

To this end, we assessed socially reinforced and non-socially reinforced learning in 40 healthy participants as well as persons with behavioural variant frontotemporal dementia (n = 21), Parkinson’s disease (n = 31) and Alzheimer’s disease (n = 20). These conditions are typified by predominant deficits in social cognition, feedback-based learning and associative learning, respectively, although all three domains may be partly compromised in the other conditions. We combined a validated behavioural task with ongoing EEG signatures of implicit learning (medial frontal negativity) and offline MRI measures (voxel-based morphometry).

In healthy participants, learning was facilitated by social feedback relative to non-social feedback. In comparison with controls, this effect was specifically impaired in behavioural variant frontotemporal dementia and Parkinson’s disease, while unspecific learning deficits (across social and non-social conditions) were observed in Alzheimer’s disease. EEG results showed increased medial frontal negativity in healthy controls during social feedback and learning. Such a modulation was selectively disrupted in behavioural variant frontotemporal dementia. Neuroanatomical results revealed extended temporo-parietal and fronto-limbic correlates of socially reinforced learning, with specific temporo-parietal associations in behavioural variant frontotemporal dementia and predominantly fronto-limbic regions in Alzheimer’s disease. In contrast, non-socially reinforced learning was consistently linked to medial temporal/hippocampal regions. No associations with cortical volume were found in Parkinson’s disease. Results are consistent with core social deficits in behavioural variant frontotemporal dementia, subtle disruptions in ongoing feedback-mechanisms and social processes in Parkinson’s disease and generalized learning alterations in Alzheimer’s disease. This multimodal approach highlights the impact of different neurodegenerative profiles on learning and social feedback.

Our findings inform a promising theoretical and clinical agenda in the fields of social learning, socially reinforced learning and neurodegeneration.

Autonomic factors do not underlie the elevated self-disgust levels in Parkinson's disease

INTRODUCTION

Parkinson's disease (PD) is manifested along with non-motor symptoms such as impairments in basic emotion regulation, recognition and expression. Yet, self-conscious emotion (SCEs) such as self-disgust, guilt and shame are under-investigated. Our previous research indicated that Parkinson patients have elevated levels of self-reported and induced self-disgust. However, the cause of that elevation-whether lower level biophysiological factors, or higher level cognitive factors, is unknown.

METHODS

To explore the former, we analysed Skin Conductance Response (SCR, measuring sympathetic activity) amplitude and high frequency Heart Rate Variability (HRV, measuring parasympathetic activity) across two emotion induction paradigms, one involving narrations of personal experiences of self-disgust, shame and guilt, and one targeting self-disgust selectively via images of the self. Both paradigms had a neutral condition.

RESULTS

Photo paradigm elicited significant changes in physiological responses in patients relative to controls-higher percentages of HRV in the high frequency range but lower SCR amplitudes, with patients to present lower responses compared to controls. In the narration paradigm, only guilt condition elicited significant SCR differences between groups.

CONCLUSIONS

Consequently, lower level biophysiological factors are unlikely to cause elevated self-disgust levels in Parkinson's disease, which by implication suggests that higher level cognitive factors may be responsible.

Guided Spatial Transformers for Facial Expression Recognition

Spatial Transformer Networks are considered a powerful algorithm to learn the main areas of an image, but still, they could be more efficient by receiving images with embedded expert knowledge. This paper aims to improve the performance of conventional Spatial Transformers when applied to Facial Expression Recognition. Based on the Spatial Transformers’ capacity of spatial manipulation within networks, we propose different extensions to these models where effective attentional regions are captured employing facial landmarks or facial visual saliency maps. This specific attentional information is then hardcoded to guide the Spatial Transformers to learn the spatial transformations that best fit the proposed regions for better recognition results. For this study, we use two datasets: AffectNet and FER-2013. For AffectNet, we achieve a 0.35% point absolute improvement relative to the traditional Spatial Transformer, whereas for FER-2013, our solution gets an increase of 1.49% when models are fine-tuned with the Affectnet pre-trained weights.

Social Cognition and Cognitive Decline in Patients with Parkinson's Disease

Social cognition (SC) comprises an array of cognitive and affective abilities such as social perception, theory of mind, empathy, and social behavior. Previous studies have suggested the existence of deficits in several SC abilities in Parkinson disease (PD), although not unanimously.

OBJECTIVE

The aim of this study is to assess the SC construct and to explore its relationship with cognitive state in PD patients.

METHOD

We compare 19 PD patients with cognitive decline, 27 cognitively preserved PD patients, and 29 healthy control (HC) individuals in social perception (static and dynamic emotional facial recognition), theory of mind, empathy, and social behavior tasks. We also assess processing speed, executive functions, memory, language, and visuospatial ability.

RESULTS

PD patients with cognitive decline perform worse than the other groups in both facial expression recognition tasks and theory of mind. Cognitively preserved PD patients only score worse than HCs in the static facial expression recognition task. We find several significant correlations between each of the SC deficits and diverse cognitive processes.

CONCLUSIONS

The results indicate that some components of SC are impaired in PD patients. These problems seem to be related to a global cognitive decline rather than to specific deficits. Considering the importance of these abilities for social interaction, we suggest that SC be included in the assessment protocols in PD.

Oral Health Disorders in Parkinson's Disease: More than Meets the Eye

Despite clinical evidence of poor oral health and hygiene in Parkinson’s disease (PD) patients, the mouth is often overlooked by both patients and the medical community, who generally focus on motor or psychiatric disorders considered more burdensome. Yet, oral health is in a two-way relationship with overall health—a weakened status triggering a decline in the quality of life. Here, we aim at giving a comprehensive overview of oral health disorders in PD, while identifying their etiologies and consequences. The physical (abnormal posture, muscle tone, tremor, and dyskinesia), behavioral (cognitive and neuropsychiatric disorders), and iatrogenic patterns associated with PD have an overall detrimental effect on patients’ oral health, putting them at risk for other disorders (infections, aspiration, pain, malnutrition), reducing their quality of life and increasing their isolation (anxiety, depression, communication issues). Interdisciplinary cooperation for prevention, management and follow-up strategies need to be implemented at an early stage to maintain and improve patients’ overall comfort and condition. Recommendations for practice, including (non-)pharmacological management strategies are discussed, with an emphasis on the neurologists’ role. Of interest, the oral cavity may become a valuable tool for diagnosis and prognosis in the near future (biomarkers). This overlooked but critical issue requires further attention and interdisciplinary research.

Anodal Transcranial Direct Current Stimulation over the Cerebellum Enhances Sadness Recognition in Parkinson's Disease Patients: a Pilot Study

Emotional processing impairments, resulting in a difficulty to decode emotions from faces especially for negative emotions, are characteristic non-motor features of Parkinson’s disease (PD). There is limited evidence about the specific contribution of the cerebellum to the recognition of emotional contents in facial expressions even though patients with cerebellar dysfunction often lose this ability. In this study, we aimed to evaluate whether the recognition of facial expressions can be modulated by cerebellar transcranial direct current stimulation (tDCS) in PD patients. Nine PD patients were enrolled and received anodal and sham tDCS (2 mA, 20 min), for 5 consecutive days, in two separate cycles at intervals of at least 1 month. The facial emotion recognition task was administered at baseline (T0) and after cerebellar tDCS on day 5 (T1). Our preliminary study showed that anodal cerebellar tDCS significantly enhanced emotional recognition in response to sad facial expressions by about 16%, but left recognition of anger, happiness, and neutral facial expressions unchanged. Despite the small sample size, our preliminary results show that anodal tDCS applied for five consecutive days over the cerebellum modulates the way PD patients recognize specific facial expressions, thus suggesting that the cerebellum plays a crucial role in recognition of negative emotions and corroborating previous knowledge on the link between social cognition and the cerebellum.

A subcortical network for implicit visuo-spatial attention: Implications for Parkinson's Disease

Recent studies in humans and animal models suggest a primary role of the basal ganglia in the extraction of stimulus-value regularities, then exploited to orient attentional shift and build up sensorimotor memories. The tail of the caudate and the posterior putamen both receive early visual input from the superficial layers of the superior colliculus, thus forming a closed-loop. We portend that the functional value of this circuit is to manage the selection of visual stimuli in a rapid and automatic way, once sensory-motor associations are formed and stored in the posterior striatum. In Parkinson's Disease, the nigrostriatal dopamine depletion starts and tends to be more pronounced in the posterior putamen. Thus, at least some aspect of the visuospatial attention deficits observed since the early stages of the disease could be the behavioral consequences of a cognitive system that has lost the ability to translate high-level processing in stable sensorimotor memories.

Masking Emotions: Face Masks Impair How We Read Emotions

To date, COVID-19 has spread across the world, changing our way of life and forcing us to wear face masks. This report demonstrates that face masks influence the human ability to infer emotions by observing facial configurations. Specifically, a mask obstructing a face limits the ability of people of all ages to infer emotions expressed by facial features, but the difficulties associated with the mask’s use are significantly pronounced in children aged between 3 and 5 years old. These findings are of essential importance, as they suggest that we live in a time that may potentially affect the development of social and emotion reasoning, and young children’s future social abilities should be monitored to assess the true impact of the use of masks.

Interoception Primes Emotional Processing: Multimodal Evidence from Neurodegeneration

Recent frameworks in cognitive neuroscience and behavioral neurology underscore interoceptive priors as core modulators of negative emotions. However, the field lacks experimental designs manipulating the priming of emotions via interoception and exploring their multimodal signatures in neurodegenerative models. Here, we designed a novel task that involves interoceptive and control-exteroceptive priming conditions followed by post-interoception and post-exteroception facial emotion recognition (FER). We recruited 114 participants, including healthy controls (HCs) as well as patients with behavioral variant frontotemporal dementia (bvFTD), Parkinson's disease (PD), and Alzheimer's disease (AD). We measured online EEG modulations of the heart-evoked potential (HEP), and associations with both brain structural and resting-state functional connectivity patterns. Behaviorally, post-interoception negative FER was enhanced in HCs but selectively disrupted in bvFTD and PD, with AD presenting generalized disruptions across emotion types. Only bvFTD presented impaired interoceptive accuracy. Increased HEP modulations during post-interoception negative FER was observed in HCs and AD, but not in bvFTD or PD patients. Across all groups, post-interoception negative FER correlated with the volume of the insula and the ACC. Also, negative FER was associated with functional connectivity along the (a) salience network in the post-interoception condition, and along the (b) executive network in the post-exteroception condition. These patterns were selectively disrupted in bvFTD (a) and PD (b), respectively. Our approach underscores the multidimensional impact of interoception on emotion, while revealing a specific pathophysiological marker of bvFTD. These findings inform a promising theoretical and clinical agenda in the fields of nteroception, emotion, allostasis, and neurodegeneration.SIGNIFICANCE STATEMENT We examined whether and how emotions are primed by interoceptive states combining multimodal measures in healthy controls and neurodegenerative models. In controls, negative emotion recognition and ongoing HEP modulations were increased after interoception. These patterns were selectively disrupted in patients with atrophy across key interoceptive-emotional regions (e.g., the insula and the cingulate in frontotemporal dementia, frontostriatal networks in Parkinson's disease), whereas persons with Alzheimer's disease presented generalized emotional processing abnormalities with preserved interoceptive mechanisms. The integration of both domains was associated with the volume and connectivity (salience network) of canonical interoceptive-emotional hubs, critically involving the insula and the anterior cingulate. Our study reveals multimodal markers of interoceptive-emotional priming, laying the groundwork for new agendas in cognitive neuroscience and behavioral neurology.

Localization and classification of human facial emotions using local intensity order pattern and shape-based texture features

Facial emotion recognition system (FERS) recognize the person’s emotions based on various image processing stages including feature extraction as one of the major processing steps. In this study, we presented a hybrid approach for recognizing facial expressions by performing the feature level fusion of a local and a global feature descriptor that is classified by a support vector machine (SVM) classifier. Histogram of oriented gradients (HoG) is selected for the extraction of global facial features and local intensity order pattern (LIOP) to extract the local features. As HoG is a shape-based descriptor, with the help of edge information, it can extract the deformations caused in facial muscles due to changing emotions. On the contrary, LIOP works based on the information of pixels intensity order and is invariant to change in image viewpoint, illumination conditions, JPEG compression, and image blurring as well. Thus both the descriptors proved useful to recognize the emotions effectively in the images captured in both constrained and realistic scenarios. The performance of the proposed model is evaluated based on the lab-constrained datasets including CK+, TFEID, JAFFE as well as on realistic datasets including SFEW, RaF, and FER-2013 dataset. The optimal recognition accuracy of 99.8%, 98.2%, 93.5%, 78.1%, 63.0%, 56.0% achieved respectively for CK+, JAFFE, TFEID, RaF, FER-2013 and SFEW datasets respectively.

Social cognitive impairment in early Parkinson's disease: A novel "mild impairment"?

INTRODUCTION

Social cognition (SC) deficit has recently been described in the early stages of Parkinson's disease (PD), but findings remain unclear. Our objective was to determine the frequency of SC impairment in newly-diagnosed PD patients and whether it is independent of Mild Cognitive Impairment (MCI).

METHODS

We enrolled 109 patients with idiopathic PD diagnosed within the previous four years (ICEBERG cohort) and 39 healthy participants. SC was evaluated using the Mini-Social Cognition and Emotional Assessment (Mini-SEA) that allows a multi-domain assessment of SC. Relationships between SC and clinical characteristics, global cognitive efficiency, mood, anxiety, apathy and impulse control disorders, were also evaluated.

RESULTS

30% of patients had significant socio-emotional impairment. Moreover, SC deficit in isolation was 3.5 times more frequent than MCI in isolation (20.2% vs 5.5% respectively). Both emotion identification and Theory of Mind were impaired compared to healthy participants. No effect of age, level of education, disease severity, dopamine replacement therapy, or global cognitive efficiency were found. Only scores on the Frontal Assessment Battery were correlated with SC abilities.

CONCLUSION

SC impairment is frequent in early PD and should be given more consideration. It often occurs in the absence of any other cognitive disorder and may represent the most common neuropsychological deficit in early-stage PD. In line with the definition of PD-MCI criteria, we consider the addition of a sixth MCI sub-type termed "Mild Social Cognition Impairment (MSCI)". Further studies are required to validate the addition of this new MCI domain.

Social Cognition in Patients with Early-Onset Parkinson's Disease

Social cognition (SC) deficits have been linked to Parkinson's disease (PD) but have been less well researched than general cognitive processes, especially in early-onset PD (EOPD), despite this population often having greater social and family demands. Most studies focus on recognition of facial emotion, theory of mind (ToM), and decision-making domains, with limited research reporting on social reasoning. The main objective of this work was to compare SC ability across four domains: emotional processing, social reasoning, ToM, and decision-making between patients with EOPD and healthy controls. Twenty-five nondemented patients with EOPD and 25 controls matched for sex, age, and educational level were enrolled. A battery that included six SC tests was administered to all study participants; a decision-making scale was completed by participants' partners. Statistically significant differences were found between patients with EOPD and controls in all subtests across the four SC domains studied. The EOPD group demonstrated worse performance on all tasks, with large effect sizes. Differences remained significant after adjusting for Montreal Cognitive Assessment (MoCA) test scores for all SC subtests except the decision-making scale and the Iowa gambling task. No significant correlations between SC and other clinical PD variables were found. Our study shows that patients with EOPD perform significantly below controls in multiple SC domains affecting recognition of facial emotion, social reasoning, ToM, and decision-making. Only decision-making seems to be mediated by overall cognitive ability. The confounding or contributing effect of other clinical PD variables should be studied further.

Hypomimia in Parkinson's Disease: What Is It Telling Us?

Introduction: Amimia is one of the most typical features of Parkinson's disease (PD). However, its significance and correlation with motor and nonmotor symptoms is unknown. The aim of this study is to evaluate the association between amimia and motor and nonmotor symptoms, including cognitive status, depression, and quality of life in PD patients. We also tested the blink rate as a potential tool for objectively measuring upper facial bradykinesia. Methods: We prospectively studied amimia in PD patients. Clinical evaluation was performed using the Unified Parkinson's Disease Rating Scale (UPDRS) and timed tests. Cognitive status, depression, and quality of life were assessed using the Parkinson's Disease Cognitive Rating Scale (PD-CRS), the 16-Item Quick Inventory of Depressive Symptomatology (QIDS-SR16), and the PDQ-39, respectively. Amimia was clinically evaluated according to item 19 of UPDRS III. Finally, we studied upper facial amimia by measuring resting blink frequency and blink rate during spontaneous conversation. Results: We included 75 patients. Amimia (item 19 UPDRS III) correlated with motor and total UPDRS (r: 0.529 and 0.551 Spearman), and its rigidity, distal bradykinesia, and motor axial subscores (r: 0.472; r: 0.252, and r: 0.508, respectively); Hoehn and Yahr scale (r: 0.392), timed tests, gait freezing, cognitive status (r: 0.29), and quality of life (r: 0.268) correlated with amimia. Blinking frequency correlated with amimia (measured with item 19 UPDRS), motor and total UPDRS. Conclusion: Amimia correlates with motor (especially axial symptoms) and cognitive situations in PD. Amimia could be a useful global marker of overall disease severity, including cognitive decline.

Parkinson's Disease: A Review from Pathophysiology to Treatment

Parkinson's Disease (PD) is the second most common neurodegenerative disease in the elderly population, with a higher prevalence in men, independent of race and social class; it affects approximately 1.5 to 2.0% of the elderly population over 60 years and 4% for those over 80 years of age. PD is caused by the necrosis of dopaminergic neurons in the substantia nigra, which is the brain region responsible for the synthesis of the neurotransmitter dopamine (DA), resulting in its decrease in the synaptic cleft. The monoamine oxidase B (MAO-B) degrades dopamine, promoting the glutamate accumulation and oxidative stress with the release of free radicals, causing excitotoxicity. The PD symptoms are progressive physical limitations such as rigidity, bradykinesia, tremor, postural instability and disability in functional performance. Considering that there are no laboratory tests, biomarkers or imaging studies to confirm the disease, the diagnosis of PD is made by analyzing the motor features. There is no cure for PD, and the pharmacological treatment consists of a dopaminergic supplement with levodopa, COMT inhibitors, anticholinergics agents, dopaminergic agonists, and inhibitors of MAO-B, which basically aims to control the symptoms, enabling better functional mobility and increasing life expectancy of the treated PD patients. Due to the importance and increasing prevalence of PD in the world, this study reviews information on the pathophysiology, symptomatology as well as the most current and relevant treatments of PD patients.

Predicting and Characterizing Neurodegenerative Subtypes with Multimodal Neurocognitive Signatures of Social and Cognitive Processes

BACKGROUND

Social cognition is critically compromised across neurodegenerative diseases, including the behavioral variant frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and Parkinson's disease (PD). However, no previous study has used social cognition and other cognitive tasks to predict diagnoses of these conditions, let alone reporting the brain correlates of prediction outcomes.

OBJECTIVE

We performed a diagnostic classification analysis using social cognition, cognitive screening (CS), and executive function (EF) measures, and explored which anatomical and functional networks were associated with main predictors.

METHODS

Multiple group discriminant function analyses (MDAs) and ROC analyses of social cognition (facial emotional recognition, theory of mind), CS, and EF were implemented in 223 participants (bvFTD, AD, PD, controls). Gray matter volume and functional connectivity correlates of top discriminant scores were investigated.

RESULTS

Although all patient groups revealed deficits in social cognition, CS, and EF, our classification approach provided robust discriminatory characterizations. Regarding controls, probabilistic social cognition outcomes provided the best characterization for bvFTD (together with CS) and PD, but not AD (for which CS alone was the best predictor). Within patient groups, the best MDA probabilities scores yielded high classification rates for bvFTD versus PD (98.3%, social cognition), AD versus PD (98.6%, social cognition + CS), and bvFTD versus AD (71.7%, social cognition + CS). Top MDA scores were associated with specific patterns of atrophy and functional networks across neurodegenerative conditions.

CONCLUSION

Standardized validated measures of social cognition, in combination with CS, can provide a dimensional classification with specific pathophysiological markers of neurodegeneration diagnoses.

Social Symptoms of Parkinson's Disease

Parkinson's disease (PD) is typically well recognized by its characteristic motor symptoms (e.g., bradykinesia, rigidity, and tremor). The cognitive symptoms of PD are increasingly being acknowledged by clinicians and researchers alike. However, PD also involves a host of emotional and communicative changes which can cause major disruptions to social functioning. These incude problems producing emotional facial expressions (i.e., facial masking) and emotional speech (i.e., dysarthria), as well as difficulties recognizing the verbal and nonverbal emotional cues of others. These social symptoms of PD can result in severe negative social consequences, including stigma, dehumanization, and loneliness, which might affect quality of life to an even greater extent than more well-recognized motor or cognitive symptoms. It is, therefore, imperative that researchers and clinicans become aware of these potential social symptoms and their negative effects, in order to properly investigate and manage the socioemotional aspects of PD. This narrative review provides an examination of the current research surrounding some of the most common social symptoms of PD and their related social consequences and argues that proactively and adequately addressing these issues might improve disease outcomes.

Impaired Recognition of Facial Emotion in Patients With Parkinson Disease Under Dopamine Therapy

INTRODUCTION

Parkinson disease (PD) is a neurodegenerative disorder characterized by motor and nonmotor symptoms. The impaired ability to recognize facial emotion expressions represents an important nonmotor symptom. The aim of this study is to investigate the ability in recognizing facial emotion expressions in patients with PD under dopamine replacement therapy.

METHODS

Thirty medicated patients with PD and 15 healthy controls (HC) were enrolled. All participants performed the Ekman 60-Faces test for emotional recognition. All patients underwent a neuropsychological evaluation for global cognitive functioning, depression, and anxiety.

RESULTS

Patients with PD were impaired in recognizing emotions. Significant differences between PD and HC were found in Ekman 60-Faces test scores (P < .001), and in Ekman 60-Faces test subscales, in particular, sadness, fear, disgust, anger, and surprise (P < .001).

CONCLUSIONS

The nigrostriatal dopaminergic depletion seems to determine emotional information processing dysfunction. This relevant nonmotor symptom could have consequences in daily living reducing interactions and social behavioral competence.

Effects of Subthalamic Nucleus Deep Brain Stimulation on Facial Emotion Recognition in Parkinson's Disease: A Critical Literature Review

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy for Parkinson's disease (PD). Nevertheless, DBS has been associated with certain nonmotor, neuropsychiatric effects such as worsening of emotion recognition from facial expressions. In order to investigate facial emotion recognition (FER) after STN DBS, we conducted a literature search of the electronic databases MEDLINE and Web of science. In this review, we analyze studies assessing FER after STN DBS in PD patients and summarize the current knowledge of the effects of STN DBS on FER. The majority of studies, which had clinical and methodological heterogeneity, showed that FER is worsening after STN DBS in PD patients, particularly for negative emotions (sadness, fear, anger, and tendency for disgust). FER worsening after STN DBS can be attributed to the functional role of the STN in limbic circuits and the interference of STN stimulation with neural networks involved in FER, including the connections of the STN with the limbic part of the basal ganglia and pre- and frontal areas. These outcomes improve our understanding of the role of the STN in the integration of motor, cognitive, and emotional aspects of behaviour in the growing field of affective neuroscience. Further studies using standardized neuropsychological measures of FER assessment and including larger cohorts are needed, in order to draw definite conclusions about the effect of STN DBS on emotional recognition and its impact on patients' quality of life.

Lateralized Deficits of Disgust Processing After Insula-Basal Ganglia Damage

A growing body of evidence suggests a role of the insular cortex (IC) and the basal ganglia (BG) in the experience, expression, and recognition of disgust. However, human lesion research, probing this structure-function link, has yielded rather disparate findings in single cases of unilateral and bilateral damage to these areas. Comparative group approaches are needed to elucidate whether disgust-related deficits specifically follow damage to the IC-BG system, or whether there might be a differential hemispheric contribution to disgust processing. We examined emotional processing by means of a comprehensive emotional test battery in four patients with left- and four patients with right-hemispheric lesions to the IC-BG system as well as in 19 healthy controls. While single tests did not provide clear-cut separations of patient groups, composite scores indicated selective group effects for disgust. Importantly, left-lesioned patients presented attenuated disgust composites, while right-lesioned patients showed increased disgust composites, as compared to each other and controls. These findings propose a left-hemispheric basis of disgust, potentially due to asymmetrical representations of autonomic information in the human forebrain. The present study provides the first behavioral evidence of hemispheric lateralization of a specific emotion in the human brain, and contributes to neurobiological models of disgust.

Alexithymia Is Associated with Reduced Quality of Life and Increased Caregiver Burden in Parkinson's Disease

Parkinson's disease (PD) is the second most frequent neurodegenerative disease of people who are beyond 50 years of age. People with PD (PwP) suffer from a large variety of motor and non-motor symptoms resulting in reduced health-related quality of life (HR-QoL). In the last two decades, alexithymia was identified as an additional non-motor symptom in PD. Alexithymia is defined as a cognitive affective disturbance resulting in difficulty to identify and distinguish feelings from bodily sensations of emotional arousal. In PD, the frequency of patients suffering of alexithymia is increased compared to healthy controls. The aim of the present study was to determine the relationship of alexithymia to HR-QoL of the PwP and caregiver burden of the corresponding caregiver. This cross-sectional questionnaire-based study used disease specific questionnaires for HR-QoL and caregiver burden. In total 119 PwP and their corresponding caregivers were included in the study. HR-QoL of the PwP correlated significantly with alexithymia (p < 0.001), especially the sub-components "identifying feelings" (p < 0.001) and "difficulties describing feelings" (p = 0.001). Caregiver burden also correlated significantly with PwP alexithymia (p < 0.001). However, caregiver burden was associated with sub-components "identifying feelings" (p < 0.008) and "external oriented thinking" (p < 0.004). These data support the importance of alexithymia as a non-motor symptom in PD.

Severity of idiopathic rapid eye movement sleep behavior disorder correlates with depression and alexithymia

BACKGROUND

Depression and alexithymia often accompany early stages of Parkinson's disease (PD). However, these symptoms in idiopathic rapid eye movement sleep behavior disorder (iRBD) remain incompletely understood. The aim of this study was to compare depression and alexithymia between iRBD patients and healthy controls, and to evaluate the association between clinical RBD severity and severity of depression and alexithymia.

METHODS

Polysomnography-confirmed iRBD patients (n = 86) and healthy controls (n = 74) were enrolled. Clinical RBD severity was assessed using the RBD questionnaire-Hong Kong (RBDQ-HK). Depression and alexithymia were evaluated by the Beck Depression Inventory (BDI) and the 20-item Toronto Alexithymia Scale (TAS-20), respectively. Multivariate linear regression analysis was performed with adjustments for several covariates to determine the correlations between RBD severity and severity of depression and alexithymia.

RESULTS

BDI scores were significantly higher in the iRBD group (10.6 ± 7.3) than in healthy controls (8.2 ± 6.0, p = 0.024). Higher total RBDQ-HK scores were associated with more severe depression in iRBD patients, even after controlling for confounding variables. iRBD patients exhibited significantly higher TAS-20 scores (45.7 ± 10.4) than healthy controls (42.1 ± 9.8, p = 0.026). Total RBDQ-HK scores were positively correlated with TAS-20 scores independent of BDI scores.

CONCLUSIONS

Patients with iRBD were more depressed and had more severe alexithymia than healthy controls. Notably, as the clinical severity of RBD increased, both depression and alexithymia worsened.